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Scalable Bayesian uncertainty quantification with data-driven priors for radio interferometric imaging
Next-generation radio interferometers like the Square Kilometer Array have the potential to
unlock scientific discoveries thanks to their unprecedented angular resolution and …
unlock scientific discoveries thanks to their unprecedented angular resolution and …
Accelerating proximal Markov chain Monte Carlo by using an explicit stabilized method
We present a highly efficient proximal Markov chain Monte Carlo methodology to perform
Bayesian computation in imaging problems. Similarly to previous proximal Monte Carlo …
Bayesian computation in imaging problems. Similarly to previous proximal Monte Carlo …
Efficient Bayesian computation for low-photon imaging problems
This paper studies a new and highly efficient Markov chain Monte Carlo (MCMC)
methodology to perform Bayesian inference in low-photon imaging problems, with particular …
methodology to perform Bayesian inference in low-photon imaging problems, with particular …
Hopf algebra structures for the backward error analysis of ergodic stochastic differential equations
E Bronasco, A Laurent - ar** efficient Bayesian computation algorithms for imaging inverse problems is
challenging due to the dimensionality involved and because Bayesian imaging models are …
challenging due to the dimensionality involved and because Bayesian imaging models are …
Conservative stabilized runge-kutta methods for the vlasov-fokker-planck equation
I Almuslimani, N Crouseilles - Journal of Computational Physics, 2023 - Elsevier
In this work, we aim at constructing numerical schemes, that are as efficient as possible in
terms of cost and conservation of invariants, for the Vlasov–Fokker–Planck system coupled …
terms of cost and conservation of invariants, for the Vlasov–Fokker–Planck system coupled …
Exotic aromatic B-series for the study of long time integrators for a class of ergodic SDE\MakeLowercase {s}
We introduce a new algebraic framework based on a modification (called exotic) of aromatic
Butcher-series for the systematic study of the accuracy of numerical integrators for the …
Butcher-series for the systematic study of the accuracy of numerical integrators for the …
Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling
This paper presents a new accelerated proximal Markov chain Monte Carlo methodology to
perform Bayesian inference in imaging inverse problems with an underlying convex …
perform Bayesian inference in imaging inverse problems with an underlying convex …
Explicit stabilised gradient descent for faster strongly convex optimisation
This paper introduces the Runge–Kutta Chebyshev descent method (RKCD) for strongly
convex optimisation problems. This new algorithm is based on explicit stabilised integrators …
convex optimisation problems. This new algorithm is based on explicit stabilised integrators …